Comparative Iron Loss Analysis of the Interior PMSMs for Electric Vehicles Considering the Effects of Temperature Variation

Liu, L; Guo, Y; Lei, G; Zhu, J

Comparative Iron Loss Analysis of the Interior PMSMs for Electric Vehicles Considering the Effects of Temperature Variation

Liu, L Guo, Y

Lei, G

Zhu, J

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD), 2024, 00, pp. 1-2
Issue Date:: 2024-01-09

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Field	Value	Language
dc.contributor.author	Liu, L
dc.contributor.author	Guo, Y https://orcid.org/0000-0001-6182-0684
dc.contributor.author	Lei, G https://orcid.org/0000-0002-8369-6802
dc.contributor.author	Zhu, J
dc.date	2023-10-27
dc.date.accessioned	2024-05-13T01:44:41Z
dc.date.available	2024-05-13T01:44:41Z
dc.date.issued	2024-01-09
dc.identifier.citation	2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD), 2024, 00, pp. 1-2
dc.identifier.isbn	9798350301571
dc.identifier.uri	http://hdl.handle.net/10453/178874
dc.description.abstract	Accurately calculating iron loss in the extensively used interior permanent magnet synchronous machines IPMSMs is challenging due to the effects of temperature variations which can also be significant in automotive applications for optimizing efficiency While the finite element method is a valuable tool for simulating and analyzing complex systems including electric vehicle EV traction motors it is essential to be aware of its limitations on computational cost and potential challenges when calculating iron loss in analyzing multi physics effects Therefore this paper presents a comparative iron loss analysis between the improved analytical iron loss calculation model finite element results and experimental measurements of an IPMSM used in EVs with a specific focus on considering the effects of temperature variation By investigating the impact of temperature changes on iron loss by these obtained data this study aims to provide valuable insights into validating the improved model s accuracy assessing its computational efficiency and identifying potential areas for improvement
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD)
dc.relation.ispartof	2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices
dc.relation.isbasedon	10.1109/asemd59061.2023.10369791
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.title	Comparative Iron Loss Analysis of the Interior PMSMs for Electric Vehicles Considering the Effects of Temperature Variation
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Tianjin, China
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	in_progress	*
dc.date.updated	2024-05-13T01:44:39Z
pubs.finish-date	2023-10-29
pubs.publication-status	Published
pubs.start-date	2023-10-27
pubs.volume	00

Abstract:

Accurately calculating iron loss in the extensively used interior permanent magnet synchronous machines IPMSMs is challenging due to the effects of temperature variations which can also be significant in automotive applications for optimizing efficiency While the finite element method is a valuable tool for simulating and analyzing complex systems including electric vehicle EV traction motors it is essential to be aware of its limitations on computational cost and potential challenges when calculating iron loss in analyzing multi physics effects Therefore this paper presents a comparative iron loss analysis between the improved analytical iron loss calculation model finite element results and experimental measurements of an IPMSM used in EVs with a specific focus on considering the effects of temperature variation By investigating the impact of temperature changes on iron loss by these obtained data this study aims to provide valuable insights into validating the improved model s accuracy assessing its computational efficiency and identifying potential areas for improvement

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http://hdl.handle.net/10453/178874